I am a software engineer who currently works on building out Presto for Capital One. Presto is a sql engine that runs on distributed data processing clusters and is optimized for latency. Because of Capital One’s petabytes and petabytes worth of data, and the strict regulations of the financial sector, building out a sql engine that balances latency and security is a non-trivial problem. My day-to-day involves building out Presto functionality to work at enterprise scale and adding features that decrease man-hours and human error.

For Capital One's data transformation journey, the maintenance of migration servers is a key factor of success. In order to prevent impediments, adequate monitoring of servers is vital for quick diagnosis of issues. My project was to implement Datadog scripts and dashboards within the servers to ensure that engineers using the servers could quickly find out root causes of server crashes and slowdowns.

Loan Syndication is a 1 trillion+ market that involves inviting groups of lenders to participate in a large loan. The act of inviting lenders to participate is a costly process that takes extensive time and labor. My project was to create a data-science and machine learning driven model of relevant factors to predict the likelihood of invited lenders of accepting a deal.